Multiscale brain modelling. Export

@article{citeulike:353139, abstract = {A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained.}, address = {School of Physics, University of Sydney, NSW 2006, Australia. p.robinson@physics.usyd.edu.au}, author = {Robinson, P. A. and Rennie, C. J. and Rowe, D. L. and O'Connor, S. C. and Gordon, E.}, citeulike-article-id = {353139}, citeulike-linkout-0 = {http://dx.doi.org/10.1098/rstb.2005.1638}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/16087447}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=16087447}, day = {29}, doi = {10.1098/rstb.2005.1638}, issn = {0962-8436}, journal = {Philos Trans R Soc Lond B Biol Sci}, keywords = {bea, database, modeling, multiscale}, month = {May}, number = {1457}, pages = {1043--1050}, posted-at = {2008-10-13 12:26:47}, priority = {2}, title = {Multiscale brain modelling.}, url = {http://dx.doi.org/10.1098/rstb.2005.1638}, volume = {360}, year = {2005} }

TY - JOUR ID - citeulike:353139 L3 - citeulike-article-id:353139 N2 - A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained. IS - 1457 JF - Philos Trans R Soc Lond B Biol Sci SN - 0962-8436 AD - School of Physics, University of Sydney, NSW 2006, Australia. p.robinson@physics.usyd.edu.au EP - 1050 TI - Multiscale brain modelling. VL - 360 SP - 1043 KW - bea KW - database KW - modeling KW - multiscale AU - Robinson, PA AU - Rennie, CJ AU - Rowe, DL AU - O'Connor, SC AU - Gordon, E PY - 2005/05/29/ UR - http://dx.doi.org/10.1098/rstb.2005.1638 ER -